16,398 research outputs found

    RELATIONSHIP BETWEEN BODY-SEAT INTERFACE PRESSURE AND DISCOMFORT DURING ROWING

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    Discomfort and pressure-related tissue injury to the buttocks are common complaints among rowers. The soft tissues of the buttocks are non-uniformly loaded during rowing. The current state of literature on seating discomfort is inconclusive as to a desirable body-seat interface pressure pattern. The purpose of this study was to determine whether localising pressure under bony protuberances or diffusing pressure over soft tissues would result in the least amount of discomfort. Force sensing arrays were used to measure body-seat interface pressures in 11 elite female rowers during rowing. Peak pressure measures were identified and pressure gradients were calculated. Discomfort was quantified using a questionnaire, and pressure data were then correlated with discomfort scores.Discomfort was weakly correlated with each of maximal pressure gradient (r=0.45) and peak pressure (r=0.43). The findings indicate pressure should be redistributed in order to avoid concentrating pressure under the bony protuberances o f the buttocks

    Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis

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    Amyotrophic lateral sclerosis (ALS) is a complex disease that leads to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWASs) have discovered relatively few loci. We developed a machine learning approach called RefMap, which integrates functional genomics with GWAS summary statistics for gene discovery. With transcriptomic and epigenetic profiling of motor neurons derived from induced pluripotent stem cells (iPSCs), RefMap identified 690 ALS-associated genes that represent a 5-fold increase in recovered heritability. Extensive conservation, transcriptome, network, and rare variant analyses demonstrated the functional significance of candidate genes in healthy and diseased motor neurons and brain tissues. Genetic convergence between common and rare variation highlighted KANK1 as a new ALS gene. Reproducing KANK1 patient mutations in human neurons led to neurotoxicity and demonstrated that TDP-43 mislocalization, a hallmark pathology of ALS, is downstream of axonal dysfunction. RefMap can be readily applied to other complex diseases

    Vagus Nerve Stimulation in Medically- Resistant Epilepsy: Efficacy and Tolerance

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    Background: Epilepsy is a common neurological disease that affects 1% of the population. One third of patients with epilepsy will not respond to antiseizure medications. The most effective treatment when a patient has medically resistant epilepsy is epilepsy surgery. Unfortunately, in many cases surgery is not possible. Neuromodulation is a therapy used in those patients and Vagus Nerve Stimulation (VNS) is the most common type. There are many studies focusing on seizure reduction using VNS, it is still unclear which patients will obtain the greatest benefits. Objective: To define the seizure response post-VNS implantation, to determine predictive factors associated with good outcomes after VNS implantation and to evaluate complications and side effects. Analysis will be completed in the total sample of VNS cases, in the paediatric subgroup, in medically resistant generalized epilepsy and pregnant women implanted with VNS. Patients & Methods: Patients with medically resistant epilepsy implanted with VNS at the London Health Science Centre-Western University, from 1997 to July 2018. Results: 1) VNS in epilepsy: 114 patients were included. Median seizure rate reduction was - 67.8% and 55.6% (n=41) had a ≥50% seizure reduction. There was a reduction of hospitalization after VNS implantation from 89.5% (n=102) to 45.6% (n=52). 5.3% (n=6) developed side effects associated with the implantation; and side effects were reported in 63.2% (n=72). 2) Paediatric Group: 22 patients were included. The median age when the VNS was implanted was 13. A ≥50% seizure reduction was achieved in 50% (n=11) and the median seizure reduction was -75%. Side effects were detected in 54.5% (n=12). 3) 46 patients were included in this study with a history of medically resistant generalized epilepsy. The mean age at implantation was 24 years-old. Of the LGS group 41.7% (n=12) of patients had an overall seizure reduction of ≥50%, and in the GGE group 64.7% (n=11) had a seizure reduction of ≥50%. There was a significant reduction of seizure-related hospital admissions. 4) Four patients and seven pregnancies were included. The median duration since implantation was 3.17 years. Three required c-sections, one related to failure to progress, the second due to pre-eclampsia and the third due to breach presentation. All babies were healthy, except one with developmental delay of unclear severity. Conclusion: 1) VNS can reduce the number of seizures by 50% in more than half of the patients implanted. VNS has shown a reduction in hospitalization. It is a safe therapy with frequent mild side effects. 2) The paediatric population obtained similar results compared to the total sample. 3) VNS should be considered as a treatment in patients with therapy resistant generalized epilepsy, especially in cases with GGE. 4) Our small sample suggests VNS is a relatively safe therapy during pregnancy, however, larger sample series should be collected

    Facial expression recognition and intensity estimation.

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    Doctoral Degree. University of KwaZulu-Natal, Durban.Facial Expression is one of the profound non-verbal channels through which human emotion state is inferred from the deformation or movement of face components when facial muscles are activated. Facial Expression Recognition (FER) is one of the relevant research fields in Computer Vision (CV) and Human-Computer Interraction (HCI). Its application is not limited to: robotics, game, medical, education, security and marketing. FER consists of a wealth of information. Categorising the information into primary emotion states only limit its performance. This thesis considers investigating an approach that simultaneously predicts the emotional state of facial expression images and the corresponding degree of intensity. The task also extends to resolving FER ambiguous nature and annotation inconsistencies with a label distribution learning method that considers correlation among data. We first proposed a multi-label approach for FER and its intensity estimation using advanced machine learning techniques. According to our findings, this approach has not been considered for emotion and intensity estimation in the field before. The approach used problem transformation to present FER as a multilabel task, such that every facial expression image has unique emotion information alongside the corresponding degree of intensity at which the emotion is displayed. A Convolutional Neural Network (CNN) with a sigmoid function at the final layer is the classifier for the model. The model termed ML-CNN (Multilabel Convolutional Neural Network) successfully achieve concurrent prediction of emotion and intensity estimation. ML-CNN prediction is challenged with overfitting and intraclass and interclass variations. We employ Visual Geometric Graphics-16 (VGG-16) pretrained network to resolve the overfitting challenge and the aggregation of island loss and binary cross-entropy loss to minimise the effect of intraclass and interclass variations. The enhanced ML-CNN model shows promising results and outstanding performance than other standard multilabel algorithms. Finally, we approach data annotation inconsistency and ambiguity in FER data using isomap manifold learning with Graph Convolutional Networks (GCN). The GCN uses the distance along the isomap manifold as the edge weight, which appropriately models the similarity between adjacent nodes for emotion predictions. The proposed method produces a promising result in comparison with the state-of-the-art methods.Author's List of Publication is on page xi of this thesis

    Foot and Ankle Impairments Affecting Mobility in Stroke

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    Introduction: Altered foot characteristics are common in people with stroke, with a third presenting with abnormal foot posture which is associated with ambulatory difficulties. Understanding the relationship between measures of foot and ankle impairment and their association with mobility and balance outcomes is therefore important; however, poor clinimetric properties of foot and ankle measures after stroke precludes evaluation of these relationships. Therefore, this research, undertaken as part of a multicentred research project, had the following aims: Study 1: To evaluate the clinimetric properties (feasibility, test–retest reliability, and clinical relevance) of measures of foot and ankle impairments, for application in people with stroke. Study 2: To examine how these measures differ between people with stroke and normal controls; and whether they are associated with mobility and balance outcomes. Methods: In Study 1, community-dwelling people with stroke, able to walk 10 m (metres), attended two testing sessions to evaluate the clinimetric properties of different foot and ankle measures. These included: static foot posture and dynamic foot loading (peak plantar pressure, PPP, contact area, CA and centre of pressure, CP) using a plantar pressure mat; isometric muscle strength using a hand-held dynamometer (HHD); peak ankle and hallux dorsiflexion and stiffness using bespoke rigs; and ankle plantarflexion spasticity using the Tardieu scale. Statistical analysis used intraclass correlation coefficients (ICCs₍₃,₁₎), standard error of measurement (SEM) and Bland–Altman plots. In Study 2, measures identified as reliable from Study 1 were incorporated in a cross-sectional study design. Participants were recruited from acute and community neurological services in East London and North Devon. Statistical analysis tested the differences between groups and between affected limbs in people with stroke. Impairment measures were evaluated using multivariate regression analysis for their association with functional outcomes: walking speed (over 10 m); Timed Up and Go (TUAG), Forward Functional Reach Test (FFRT) and presence of falls (> 1 in the last 3 months). Results: In Study 1, 21 people with stroke tested the measures. These were found to be feasible and easy to administer, although loss of data (up to 33%) was observed. All measures had moderate to excellent test–retest reliability (coefficients 0.50‒0.98), except ankle plantarflexion stiffness (ICCs₍₃,₁₎ = 0.00‒0.11). In Study 2, there were significant differences in all measures between people with stroke (n = 180) and controls (n = 46), apart from static foot posture (p = 0.670), toe deformity (p = 0.782) and peak hallux dorsiflexion (p = 0.320). Between limb differences were identified for all measures except foot posture (p = 0.489) and foot CA (p > 0.05). Multicollinearity analysis found 10 measures appropriate for multivariate regression which identified the following R² and variance explained: 59% walking speed (R² = 0.543); 49% TUAG (R² = 0.435); 36% FFRT (R² = 0.285) and 26% for Falls Presence. Conclusion: The study demonstrated that seven foot and ankle measures of impairment after stroke were clinically feasible, reliable and associated with mobility and balance outcomes. The measures were ankle and foot isometric muscle strength, sway velocity, PPP (RFT and FFT), CA (MFT and FFT) and peak ankle dorsiflexion. These measures can now be incorporated into research to examine methods to improve the treatment of foot and ankle after stroke
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